Model-based analysis of chromatin interactions from dCas9-Based CAPTURE-3C-seq

Area of Science:

• Genomics and Molecular Biology
• Computational Biology and Bioinformatics

Background:

• Understanding long-range chromatin interactions is essential for explaining gene expression patterns.
• Existing methods for identifying these interactions can be limited in resolution or scope.

Purpose of the Study:

• To present C3S, a statistical model and computational pipeline for analyzing CAPTURE-3C-seq data.
• To enable high-resolution identification of locus-specific, long-range DNA interactions from raw sequencing reads.

Main Methods:

• Developed a flexible pipeline (C3S) integrating statistical modeling for CAPTURE-3C-seq data analysis.
• Implemented automated bin size definition based on dCas9 binding peaks.
• Supported analysis of both intra- and inter-chromosomal interactions across mammalian cell types.

Main Results:

• Successfully applied C3S to human K562 cells and mouse embryonic stem cells (mESC) datasets.
• Detected known and novel chromatin interactions at multiple scales.
• Provided insights into developmental gene regulation at the human β-globin locus and enhancer-promoter interactions in mESCs regulating OCT4.

Conclusions:

• C3S is a robust tool for processing and analyzing CAPTURE-3C-seq data, facilitating the study of chromatin architecture.
• The pipeline aids in understanding gene regulation mechanisms, including developmental processes and pluripotency gene networks.